Towards Inverse Uncertainty Quantification in Software Development (Short Paper)
Contributo in Atti di convegno
Data di Pubblicazione:
2017
Citazione:
Towards Inverse Uncertainty Quantification in Software Development (Short Paper) / M. Camilli, A. Gargantini, P. Scandurra, C. Bellettini (LECTURE NOTES IN COMPUTER SCIENCE). - In: Software Engineering and Formal Methods / [a cura di] A. Cimatti, M. Sirjani. - [s.l] : Springer, 2017 Jul. - ISBN 9783319661964. - pp. 375-381 (( Intervento presentato al 15. convegno International Conference on Software Engineering and Formal Methods (SEFM) tenutosi a Trento nel 2017 [10.1007/978-3-319-66197-1_24].
Abstract:
With the purpose of delivering more robust systems, this paper revisits the problem of Inverse Uncertainty Quantification that is related to the discrepancy between the measured data at runtime (while the system executes) and the formal specification (i.e., a mathematical model) of the system under consideration, and the value calibration of unknown parameters in the model. We foster an approach to quantify and mitigate system uncertainty during the development cycle by combining Bayesian reasoning and online Model-based testing.
Tipologia IRIS:
03 - Contributo in volume
Elenco autori:
M. Camilli, A. Gargantini, P. Scandurra, C. Bellettini
Link alla scheda completa:
Titolo del libro:
Software Engineering and Formal Methods